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This article mainly explains "what are the key technologies of Python". The content of the explanation is simple and clear, and it is easy to learn and understand. Please follow the editor's train of thought to study and learn what the key technologies of Python are.

01. Brief introduction to Python what is Python

An object-oriented advanced dynamic interpretable scripting language.

The Python interpreter reads one line of code at a time, interprets it as a low-level machine language, such as bytecode, and executes it.

As a result, the language often causes run errors.

Why choose Python (advantage)

Python is currently the most popular language because it is easier to code and has strong interpretability.

Python is an object-oriented programming language, which can also be used to write some functional code.

Python is a good way to bridge the gap between business and developers.

Compared with other languages such as C#/Java, Python programs have been on the market for less time.

Python comes with a large number of machine learning and analysis packages.

A number of communities and books are available to support Python developers.

Almost all types of applications, from predictive analysis to UI, can be implemented in Python.

Python programs do not need to declare variable types. As a result, the applications built can run faster.

Why not choose Python (disadvantage)

Compared to other languages, Python programs run more slowly because of the lack of support similar to the Just In Time optimizer in Python.

The blank constraint of Python syntax brings some difficulties to novice coding.

Python does not provide advanced statistical capabilities like the R language.

Python is not suitable for low-level system and hardware interaction.

How Python works

The following figure shows how Python works on the machine. The key here is the interpreter, which is responsible for compiling the high-level Python language into a low-level machine language for easy understanding.

02. Variable-target type and scope

Variables that can be used in a program store information, such as saving user input, the local state of the program, and so on.

Variables in Python are named after names.

Variable types in Python include numbers, strings, collections, lists, tuples, and dictionaries, which are standard data types.

Declare and assign a value to a variable

This is as follows: first, assign the integer value 1 and the string "Hello You" to the variable myFirstVariable. Because the data types in Python are dynamic, this repeated assignment is possible.

The variable assignment operation in Python is also called blinding.

Numerical type

As shown below, Python supports integer, decimal, and floating point data.

In addition, long integers are also supported, with L as the suffix, such as 999999999999L.

String

A string is a sequence of letters that represents text information.

The value of the string is enclosed in quotation marks, as shown below.

Strings are immutable and cannot be modified once created. As follows:

When a string variable is assigned a new value, Python creates a new target to store the variable value.

Local and global variables

Local variable

A local variable, such as declaring a variable within a function, exists only in that function.

Local variables are inaccessible externally, as shown below.

The if-else and for/while loop modules in Python cannot create local variables, as shown in the for/while loop:

The output is:

In the if-else module:

Output as

All variables

Global variables can be accessed through any global function, and they exist in the _ _ main__ framework.

In addition, you can declare a global variable outside the function. It is worth noting that when you need to assign a new value to a global variable, you must use the "global" keyword, as follows:

When removing "Global TestMode", you can only set the variable to False in the some_function () function. If you want to share a global variable among multiple modules, you need to create a shared module file. Such as configuration.py, and find the variables you need in the file. Finally, import the sharing module.

View variable types

Check the face change type through the type () function, as shown below.

Commas in integer variables

A comma can be thought of as a sequence of variables, as shown below.

03. Operation numeric operation

Python supports basic numerical calculations of addition, subtraction, multiplication and division, as well as floor division (floor division), as shown below.

In addition, Python supports exponential operations (*), as shown below.

At the same time, Python can also perform division and remainder operations, as shown below.

String operation

String concatenation

String copy

String slicing

String reverse order

Negative index

If you want to get the last character of the string, you need to use a negative index, as shown below.

View index value

Regular expression

Split (): splits a string into a list through a regular expression.

Sub (): replace the character you want to match with a regular expression.

Subn (): replaces the character to be matched with a regular expression and returns the number of characters to be replaced.

Casting

Str (x): converts variable x to string type

Int (x): converts the variable x to an integer

Float (x): convert variable x to floating point

Set operation

A collection is an unordered collection of data that defines a collection variable, as shown below.

Set intersection

Gets the common portion of the two collections, as shown below.

Set difference

Get the different parts between the two collections, as shown below.

Set union

Gets the union of the two collections, as shown below.

Ternary operator

For writing conditional statements on one line, the syntax structure is [If True] if [Expression] Else [If False], as shown below.

04. Notes

Single-line comment

Multiline comment

05. Expression

Can be used for Boolean operations, such as:

Equality:==

Not Equity Equity

Greater: >

Less:=

Less or Equal:

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